Rogo Alternatives for Real Estate Investment Teams

Strengths

• Give the terminal an assignment and the deal’s files, including scans. Get Excel workbooks with live formulas, Word memos in your format, decks, and assembled PDFs. The analyst reviews and approves each key step.
• Build an Excel underwrite from unit-level rent roll data traced to file, sheet, and row. Switch between Base, Upside, and Downside. Compare each proposed assumption with the current value before accepting it, or edit a cell yourself. A second analyst can work beside you. The terminal uses your changes on its next pass, and the workbook opens cleanly in Excel.
• Drafts the screening, IC, and credit memo in the firm’s own voice, every figure from the model or footnoted to a cited document, inferred values marked. The memo opens ready to mark up, with every change tracked under your name, the terminal’s own edits included.
• Keep closing conditions in one checklist, with a responsible party and date. Reconcile the settlement statement and true up the model’s basis. Compare each ownership period with budget and the original underwrite. Preserve dated phase snapshots while the model stays live.

Trade-offs

• The deal file is the boundary. Drop any document on the deal, link the SharePoint, OneDrive, Dropbox, or Box folder you already use, or file the broker’s attachments from Outlook; the terminal does not look past those folders. There is no market data, comp, or research subscription behind it, so those feeds stay where they are.
• Not a pipeline CRM or system of record for sourcing: no contact management, broker coverage tracking, or deal-flow funnel.
• Two tiers and no published dollar figures. Pro is for funds and deal teams of up to 50 people, up and running with live deals within 24 hours. Enterprise deploys into the firm’s own AWS account, with single sign-on and customer-held keys. Evaluation runs through a working session on one live deal rather than a self-serve trial.

Strengths

• The Matrix grid returns tabular answers across large document sets with a source citation behind every cell; the company reports more than 1.5 billion pages processed to date.
• Reads market content through FactSet, S&P Capital IQ, PitchBook, Preqin, Bloomberg, and Third Bridge, with deal-room content flowing in through SS&C Intralinks.
• Over a third of the world’s largest asset managers by assets are customers, KKR and MetLife among them, and analysis converts into slide decks.

Trade-offs

• Nothing in its public materials describes rent roll or T-12 ingestion, property-level underwriting, or any structured CRE deal stage from screening through closing and the hold.
• Model output is a generated Excel export from document synthesis; a third-party comparison notes it does not evaluate formulas in the platform, so it shows the source behind a claim but not the math behind a figure.
• Enterprise contracts only, with third-party reports of roughly $10,000 per seat per year for the professional tier, on a shared service with no per-customer isolated deployment described.

Strengths

• A wide content universe: filings, broker research from more than 1,700 providers, earnings calls, news, and over 240,000 expert call transcripts.
• Deep Research works the corpus on its own with sentence-level citations, and SuperAnalyst, in early access as of June 2026, keeps research and monitoring running without being asked.
• Standardized financials on more than 22,000 companies and a library of pre-built company models, the Carousel acquisition brings AI model work directly into Excel, and a firm’s internal research can be searched alongside the market content.

Trade-offs

• Real estate is not among its listed industries as of September 2026, and its content universe carries no property documents: nothing in its materials describes rent rolls, T-12s, or lease abstracts.
• The Excel modeling is built around public-company models, not property cash flows, and no underwriting, closing, or asset-management workflow appears anywhere in its materials.
• Procurement data puts the median contract near $18,000 a year, with enterprise contracts above $100,000, and expert calls and private cloud priced as add-ons.

Strengths

• Speaks to private markets buyers directly, real estate firms named among them, with a sourcing-through-reporting frame rather than a general assistant pitch.
• Routes work across major AI providers, and plugs into the systems these firms already run, including DealCloud, Salesforce, and Microsoft 365.
• Datasite ownership gives it a data-room distribution channel, SOC 2 Type II standing, and a 2026 Private Equity Wire European award for AI innovation.

Trade-offs

• Does not build financial models or run structured underwriting; rent rolls, T-12s, and proformas sit outside what its public materials describe.
• Real estate is one audience among several rather than the center of gravity, and CRE-specific depth is not documented.
• It competes on synthesis and drafting rather than on the work product of an underwrite, so expect to validate the fit in evaluation rather than from documentation.

Strengths

• Ready-to-run templates spanning pitch building, earnings review, model building, valuation review, KYC screening, and month-end close.
• Lives where the work already is: the Excel, PowerPoint, and Word add-ins are generally available, Outlook is in beta, and context carries across them in a single session.
• Connected to FactSet, S&P Capital IQ, MSCI, PitchBook, Morningstar, Moody’s, and LSEG, with JPMorganChase, Goldman Sachs, and Citibank named as customers and no training on customer data by default.

Trade-offs

• No CRE workflow: none of its announcements mention rent rolls, T-12s, or property-level underwriting, and the model builder works from filings and data feeds, not operating statements.
• No deal lifecycle: it offers templates and add-ins, not stages from screening through closing and the hold, and no per-deal workspace or deal memory is described.
• Credit memo drafting is named as a banking use case, but nothing in its materials describes firm-specific memo formats or calibration to a house voice.